AI requires interdisciplinary teams, Quality Data & Explainability

Artificial Intelligence and Machine Learning projects require interdisciplinary skills in devops, SW engineering in addition to hard core data science coding skills. Additionally, lot of rigor needs to be put into cleaning up the data that is fed into the models. On an interesting note, AI models can also be used for improving data quality as well. Lastly, Explainability of models and data is becoming important and as such explainability needs to be baked in.

Om Podcasten

The primary goal of Data Transformers podcast is to accelerate digital transformation by bridging the gap between business goals and technology initiatives using Data as glue. Visit https://datatransformerspodcast.com for more details. With the rapid advancement of technologies such as AI, ML, IOT, Cloud computing et al and the explosion of data that these technologies rely on, it is absolutely important to manage the data in intelligent and efficient ways. We’d like to enable that by interviewing the transformers in the industry who are leading the way in digital transformation. We also would like to bring our perspectives, latest trends and most valuable resources to you so you could be a data transformer in your organization.